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Comparison of Data Access and Integration Technologies in the Life Science Domain. 19 th September 2005. Derek Houghton Database Manager Human Genetics Unit Medical Research Council Edinburgh d.houghton@hgu.mrc.ac.uk. Dr Richard Sinnott Technical Director National e-Science Centre |||

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Comparison of data access and integration technologies in the life science domain
Comparison of Data Access and Integration Technologies in the Life Science Domain

19th September 2005

Derek Houghton

Database Manager

Human Genetics Unit

Medical Research Council

Edinburgh

d.houghton@hgu.mrc.ac.uk

Dr Richard Sinnott

Technical Director National e-Science Centre

|||

Deputy Director Technical Bioinformatics

Research Centre

University of Glasgow

ros@dcs.gla.ac.uk


Life sciences and grids
Life Sciences and Grids the Life Science Domain

  • Extensive Research Community

    • >1000 per research university

  • Extensive Applications

    • Many people care about them

      • Health, Food, Environment, …

  • Interacts with many disciplines

    • Physics, Chemistry, Maths/Statistics, Nano-engineering, …

  • Huge and expanding number of databases relevant to bioinformatics community

    • Heterogeneity, Interdependence, Complexity, Change, Dirty…

  • Linking using in co-ordinated, secure manner full of open issues to be addressed

  • Compute demands growing as more in-silico research undertaken


Database growth
Database Growth the Life Science Domain

PDB Content Growth

  • DBs growing exponentially!!!

    • Biobliographic (MedLine, …)

    • Amino Acid Seq (SWISS-PROT, …)

    • 3D Molecular Structure (PDB, …)

    • Nucleotide Seq (GenBank, EMBL, …)

    • Biochemical Pathways (KEGG, WIT…)

    • Molecular Classifications (SCOP, CATH,…)

    • Motif Libraries (PROSITE, Blocks, …)


Distributed and heterogeneous data
Distributed and Heterogeneous data the Life Science Domain

Function

Structure

Sequence

LPSYVDWRSA GAVVDIKSQG ECGGCWAFSA IATVEGINKI TSGSLISLSE QELIDCGRTQ NTRGCDGGYI TDGFQFIIND GGINTEENYP YTAQDGDCDV

Gene expression

Morphology


More genomes

Arabidopsis the Life Science Domain

thaliana

Buchnerasp.

APS

Yersinia

pestis

Aquifex

aeolicus

Archaeoglobus

fulgidus

Borrelia

burgorferi

Mycobacterium

tuberculosis

Vibrio

cholerae

Caenorhabitis

elegans

Campylobacter

jejuni

Chlamydia

pneumoniae

Drosophila

melanogaster

Escherichia

coli

Neisseria

meningitidis

Z2491

Plasmodium

falciparum

Ureaplasma

urealyticum

Helicobacter

pylori

Mycobacterium

leprae

Pseudomonas

aeruginosa

mouse

Bacillus

subtilis

Thermotoga

maritima

Xylella

fastidiosa

Rickettsia

prowazekii

Saccharomyces

cerevisiae

Salmonella

enterica

rat

More genomes …...

Thermoplasma

acidophilum


Systems biology

+ links to plant/crops, environmental, health, … information sources

Systems Biology

Tissues

Cell

Organs

Protein functions

Protein Structures

Organisms

Physiology

Gene expressions

Populations

Nucleotide structures

Cell signalling

Nucleotide sequences

Protein-protein interaction (pathways)


Is grid the answer
Is Grid the Answer? information sources

  • Some key problems to be addressed

    • Tools that simplify access to and usage of data

      • Internet hopping is not ideal!

    • Tools that simplify access to and usage of large scale HPC facilities

      • qsub [-a date_time] [-A account_string] [-c interval] [-C directive_prefix] [-e path] [-h] [-I] [-j join] [-k keep] [-l resource_list] [-m mail_options] [-M user_list] [-N name] [-o path] [-p priority] [-q destination] [-r c] [-S path_list] [-u user_list] [-v variable_list] [-V] [-W additional_attributes] [-z] [script]

    • Tools designed to aid understanding of complex data sets and relationships between them

      • e.g. through visualisation

    • Make it all easy to use!

      • Scientists should not have to be Linux script experts,

      • …nor set up/configure complex Grid software or follow complex procedures for getting,

        using Grid certificates,

      • …nor have detailed understanding of low level data schemas for all data sites,

      • … etc etc


Overview of bridges
Overview of BRIDGES information sources

  • Biomedical Research Informatics Delivered by Grid Enabled Services (BRIDGES)

    • NeSC (Edinburgh and Glasgow) and IBM

    • Started October 2003 – due to end soon

  • Supporting project for CFG project

    • Generating data on hypertension

    • Rat, Mouse, Human genome databases

  • Variety of tools used

    • BLAST, BLAT, Gene Prediction, visualisation, …

  • Variety of data sources and formats

    • Microarray data, genome DBs, project partner research data, …

  • Aim is integrated infrastructure supporting

    • Data federation

    • Security


Bridges project

VO Authorisation information sources

Information Integrator

OGSA-DAI

Magna Vista Service

SyntenyService

blast

+

+

+

BRIDGES Project


Primary bridges data use case
Primary BRIDGES Data Use Case information sources

  • Givengene name/identifier, issue a query to federated database and present all available information back to the user in a user friendly/configurable way

  • Several client side applications were developed for this purpose:

    • MagnaVista, GeneVista, “JOS-AHM-vista”

      • MagnaVista and “JOSAHM-vista” are Java applications

      • GeneVista based upon portlet technologies

    • Notes

      • focus was on developing working solutions for scientists and not to compare OGSA-DAI and IBM II

      • several team changes throughout project


Overview of data access and integration technologies
Overview of Data Access and Integration Technologies information sources

  • Overview of Information Integrator

    • suite of wrappers for relational (Oracle, DB2, Sybase, …) and non-relational (flat files, Excel spreadsheets, XML databases, …) targets which extend integration capabilities of DB2 database

      • allows to establish ‘federated’ view of distributed data allowing applications access to data as though in single, local DB2 database

      • free for academic use (IBM Scholars program)

      • comes with suite of tools and utilities with which DB administrator can monitor and optimize database

      • can interact with DB either by command line or graphical interface

      • options to create Java/SQL stored procedures and customized functions


Overview of data access and integration technologies1
Overview of Data Access and Integration Technologies information sources

  • Overview of OGSA-DAI middleware

    • provides application developers with a range of service interfaces allowing data access and integration via the Grid

    • OGSA-DAI is not a database management system

      • rather it uses Grid infrastructure to perform queries on a set of relational/non-relational data sources and conveys result sets back to the user application via SOAP

      • Through OGSA-DAI interfaces, disparate, heterogeneous data sources and resources can be treated as a single logical resource

    • OGSA-DAI is

      • free/open source

      • has number of data source types both relational and non-relational with which it can communicate

    • OGSA-DAI documentation is clear/concise

    • (We’ve had!) good support from the development team


Comparing data access and integration technologies
Comparing Data Access and Integration Technologies information sources

  • How to compare?

    • Set-up installation

    • Post-installation

    • Initial user experiences

    • Challenges of life sciences

      • Schema Changes

      • Data Independence

    • Creating Federated Views

    • Performance


Set up installation
Set-Up Installation information sources

  • IBM Information Integrator

    • Process of accessing, obtaining, installing and configuring IBM II is non-trivial

      • Access through “Scholar’s Program” can be a time consuming procedure and requires authorisation

    • Advanced knowledge of the vendor clients that the wrappers may use (e.g. Sybase 12.5ASE Client) eases the installation process

      • especially true on Linux as need to manually edit config. files/run rebinding scripts if clients installed later

    • BRIDGES team also went on training course from IBM which helped

  • OGSA-DAI

    • is (by contrast) a much friendlier affair

    • one visits the download site, signs up for access and is issued with a username and password for authentication to the download area

    • new releases are advertised by email (submitted during the sign up process)

    • all downloads supplied with obligatory README file which provides

      • guidance as to the setup procedure and additional downloads needed

        • e.g. JDBC drivers, apache utilities

    • With OGSA-DAIv4 release the install process can also be done via a GUI


Post installation
Post-Installation information sources

  • IBM Information Integrator

    • IBM provides MANY!!!!! Redbooks available on their website

    • at the time of BRIDGES work in applying IBM II, these were not descriptively named so it was a matter of opening each one to discover title/topics dealt with

      • time consuming searching for specific information

    • Online search facility useful especially for syntax questions

    • Within the last few months, navigation around IBM’s website has improved significantly providing easier access to online documentation and resources

  • OGSA-DAI

    • comes with its own HTML documentation which can be downloaded separately as required

    • content and navigability of this has improved over each release as more detailed coding examples have been given

    • User support is quick and efficient with a response time typically < 24 hours


Basic usage experience
Basic Usage Experience information sources

  • IBM Information Integrator

    • Attempts were made initially to use IBM II’s XML wrapper to query Swissprot/Uniprot DB

      • DB is in XML format and available for ftp download (over 1.1GB)

      • wrapper failed in its attempt to work with this file, as, according to IBM white paper the whole document is loaded in memory as a Document Object Model (DOM)

        • Could have split the file into chunks but cumbersome solution

    • Decided to parse the file and import it into DB2 relational tables

      • Each flat file wrapper has to be manually configured to match the file ‘columns’

        • no greater effort to actually write a programme to parse the file and then add to DB

          • Once in DB have all the benefits of indexing, optimisation etc

      • initial parse of the Swissprot DB used table ‘Inserts’ to commit data immediately to DB2 database as file read by the parsing program

        • Java SAX parsing used and primary and foreign keys updated using insert triggers

        • took 84 hours for the 1.1GB file with around 500,000 inserts to the database

    • Wrapper format inconsistencies, e.g. OMIM


Basic usage experience ctd
Basic Usage Experience …ctd information sources

  • IBM Information Integrator

    • IBM II insists that the flat file being wrapped exists on a computer with exactly the same user setup/privileges as the data server itself

      • not the case with the BRIDGES federated data Grid!!

        • unlikely to be the case with other life science data sets…???

      • Fine grained security model something explored within BRIDGES based upon PERMIS technology

        • (see demo at NeSC booth for more info)


Basic usage experience ctd1
Basic Usage Experience …ctd information sources

  • OGSA-DAI

    • Used basic Perform documents for doing federated queries

    • Returned data stored locally (in files) and accessed by client application and rendered to users

    • Is this Integration?

      • From client perspective, they see no difference!!!

        • More elegant solution would be to have middleware do “integration” but issues…


Schema changes
Schema Changes information sources

  • In BRIDGES two-relational data sources allowed programmatic access:

    • Ensembl (MySQL - Rat, Mouse and Human Genomes, Homologs and Database Cross Referencing)

    • MGI (Sybase - mainly Mouse publications and some QTL data.)

  • Flat files downloaded for

    • RGD (Rat Genome Database), OMIM (Online Mendelian Inheritance in Man), Swissprot/Uniprot, HUGO (Human Gene Ontology), GO (Gene Ontology)

      • Don’t expect to be give schema for flat file!!!

  • Changes made to schema of third party DB completely out of our control

    • Ensembl change the name of their main gene database every month!

      • DB schema drastically altered on 3 occasions during BRIDGES project

    • MGI have had one major overhaul of all their table structure

  • In these cases queries to these remote data sources will fail!!!


Schema changes ctd
Schema Changes …ctd information sources

  • We used Materialized Query Tables (MQTs) in IBM II to insulate queries from remote schema changes

    • MQT is local cache of remote table/view and can be set to refresh after a specified time interval or not at all

      • up to the minute data (refreshed frequently) vs slightly older data but impervious to schema changes

    • MQT can be optimized to try the remote connection first, if available run query, if not use local cache

      • Query fails if remote schema changes!!!

  • Bridges_wget application

    • checks for remote DB connections

      • if the connection made – runs sample query naming columns to see if schema has changed

        • If all is well, remote flat files are checked for modification dates

        • If newer ones found they are downloaded, parsed and loaded into the DB

          • Goes some way to keeping the BRIDGES DB up to date with current data

        • Parsers are not semantically intelligent so require updating the code (Java) to meet with file format modifications


Data independence
Data Independence information sources

  • Key issue challenge is fact that data sources largely independent

    • Not always possible to find column to act as foreign key over which joining two (or more) databases can occur

    • When there is a candidate, often the column name is not named descriptively to give clue as to which database might be joined to which

    • For example, in case of Ensembl a row containing a gene identifier contains a Boolean column indicating whether a reference exists in another database

      • RGD_BOOL=1 indicates that a cross reference can be made to the RGD database for this gene identifier

        • Must query Ensembl RGD_XREF table to obtain unique ID for entry in RGD database

        • Query to RGD may contain references to other databases and indeed back to Ensembl

          • …potentially have circular referencing problem!!!

      • Solved by caching all available unique identifiers and their associated database from all remote data sources in local materialized query table

        • When match found, associated data resource queried and all results returned to user

          • Up to user to decide which information to use


Creating federated views
Creating Federated Views information sources

  • In setting up federated view with IBM II various steps needed:

    • choose which wrapper to use;

    • define a ‘Server’ containing all connection parameters;

    • create ‘Nicknames’ for the server

      • local DB2 tables mapped to their remote counterparts;

  • ‘Discover’ function supports this process

    • connects to the remote resource and displays all the metadata available

  • Such advanced features are not available with OGSA-DAI


Performance comparison
Performance Comparison information sources

  • Example of single query response, we ran a search for the PAX7 gene across the BRIDGES federated view of 7 bio databases. This returned

    • One entry from Ensembl Mouse Table (27 columns)

    • One entry from Ensembl Human Table (27 columns)

    • One entry from the HUGO database (20 columns)

    • Eighty five entries from MGI including full abstract and publication details. (11 columns)

    • One full entry from the OMIM database including fully annotated publication details. (19 columns)

    • Two full entries from Swissprot/Uniprot including full sequence and reference data. (50 columns)

  • The average response time for MagnaVista was 44 sec

    • includes time to rebuild the application perspective GUI

  • OGSA-DAI solutions are of this order also


Conclusions
Conclusions information sources

  • Big advantage of using IBM II is all utilities that come with database management system. This includes :

    • replication of databases which can be configured to update from single transaction committed to a set time interval for bulk updates;

    • creation of explain tables which will graphically show the query author the amount of table scans done as the result of the executed query and thereby allow different solutions to be compared;

    • creation of tasks which can be executed immediately or at specified times, e.g. when the database is less used;

    • running statistics and reorganizing tables;

    • taking Snapshots of the database to see where bottlenecks may be occurring.

  • OGSA-DAI as used in BRIDGES has shown we can implement data “access” solutions also

    • Less overheads in learning DB2

  • We note that since our evaluations were made, IBM have prototyped an OGSA-DAI wrapper for Information Integrator.


Conclusions1
Conclusions information sources

  • We focused largely on data access (and not integration)

    • Client apps took care of majority of the data integration issues

  • Tried to explore OGSA-DQP but without immediate success

    • Changes in personnel, keeping IBM II solution alive!

  • Future challenges and recommendations

    • standards/data models crucial to data access and integration

    • often gaining access to the database itself most often not possible

      • JDSS report describes these issues in detail

  • BRIDGES queries fairly simplistic in nature – returning all data sets associated with a named gene

    • GEMEPS project looking towards more complex queries,

      • e.g. lists of genes that have been expressed and their up/down expression values as might arise in microarray experiments

      • Collaboration with Cornell and Riken Institute, Japan

  • BRIDGES to be refined/extended and used within the (not so!) recently funded Scottish Bioinformatics Research Network


Comparison of data access and integration technologies in the life science domain
DEMO information sources